clear
%% Problem
%   'EqualMinima','Himmelblau','Sixhump','ModifiedRastrigin','Vincent',
%   'Shubert','Composition','IncreasingMinima','Rastrigin','Schaffer'.
ProblemSet.FuncType = 'Shubert';
ProblemSet.dimension = 2;
% ProblemSet.k = [3,3,3];
% ProblemSet.BaseFunc = 3;

[d, x_bound, ObjFunc, OptSet, precision_init, precision, ~, MaximalBudget, FileName]...
    = problem_setting(ProblemSet);

MaximalBudget = [500,1000,2000,3000,4000,5000,6000,7000,8000,9000,10000,12000];
iepsilon = 4;
epsilon = [0.1,0.01,0.001,0.0001];
OptSet.epsilon = epsilon(iepsilon);

%% problem
Problem.Dimension = d;
Problem.Domain = reshape(x_bound,[1,d*2]);
Problem.Sampling = @(n, region)Sampling_BoxConstraint(n, region, ObjFunc);
NewRegionNum = 2;
MaxPartitionDepth_d = ceil(log((x_bound(2,:)-x_bound(1,:))./precision_init)./log(NewRegionNum));
MaxPartitionDepth = sum(MaxPartitionDepth_d);
Problem.Partition = @(Region,SampleSet)Partition_BoxConstraint(Region, NewRegionNum, MaxPartitionDepth, SampleSet);
%% Algorithm
AlgorithmM.n0 = 5;
AlgorithmM.QuantileLevel = 0.2;
AlgorithmM.NewBudget = 3;
AlgorithmM.MaxSampleSize = 10;%5*(d+1);
ClearRadius0 = (x_bound(2,:)-x_bound(1,:))./(NewRegionNum.^(MaxPartitionDepth_d));
ClearRadius = 2*min(ClearRadius0); % the maximum distance within a non-partitionable region
AlgorithmM.radius = ClearRadius;
AlgorithmM.local_search = @(starts,step,MaximalBudget)LocalSearch_test(ObjFunc,x_bound,starts,step,precision(iepsilon)/2,OptSet,MaximalBudget);
%% OPTIMIZATION
rep = 100;
OptObtained = zeros(rep,length(MaximalBudget));
TotalBudget1 = zeros(rep,length(MaximalBudget));
TotalBudget2 = zeros(rep,length(MaximalBudget));
OptNoFound = zeros(rep,length(MaximalBudget));
Times = zeros(rep,length(MaximalBudget));
OptRemain = cell(rep,length(MaximalBudget));
%%
for j = 1:length(MaximalBudget)
    AlgorithmM.StopCriteria = [1,MaximalBudget(j)];
    for i=1:rep
        disp(['epsilon: ',num2str(epsilon(iepsilon)),', replication: ',num2str(i),'.'])
        tic
        [optima, ~, SampleSet, ~, ls_budget, OptSetRemain]...
            = prsmmo_ls_test( Problem, AlgorithmM, OptSet );
        Times(i,1) = toc;
        disp(['time used: ',num2str(Times(i,1)),'.'])
        OptObtained(i,j) = size(optima,1);
        TotalBudget2(i,j) = ls_budget;
        TotalBudget1(i,j) = size(SampleSet,1) - ls_budget;
        OptRemain{i,j} = OptSetRemain;
        OptNoFound(i,j) = size(OptSetRemain,1);
    end
end
%%
clear i iepsilon OptSetRemain SampleSet ls_budget optima
FileName = ['Shubert2D_a',num2str(AlgorithmM.QuantileLevel),'.mat'];
save(FileName)
a=[mean(TotalBudget1)',mean(TotalBudget2)',mean(TotalBudget1+TotalBudget2)',var(TotalBudget1+TotalBudget2)'];
%% figures
OptNum = size(OptSet.sol,1);
FoundPerc = OptNum-mean(OptNoFound);

figure()
plot(MaximalBudget, FoundPerc)
xlabel('Total Budget')
ylabel('PR')
legend(['\alpha = ',num2str(AlgorithmM.QuantileLevel)])
set(gca,'Fontname','Times New Roman','FontSize',16);
